An Effective Approach for Identifying Evolving Three-Dimensional Structural Motifs in Protein Folding Data

Molecular Dynamics-based simulations have been employed to study the protein folding process, in which a protein acquires its functional three-dimensional structure. This has resulted in a large number of protein folding trajectories. As a result, it becomes increasingly important to analyze such data to facilitate a deeper understanding of the protein folding mechanism. In this paper, we focus on identifying important 3D structural motifs in the folding data. We have proposed a multi-step algorithm that is not only computationally efficient but also captures the evolving nature of the folding process. Empirical evaluation demonstrates that such motifs are effective at characterizing a protein’s structural evolution in its folding process. We also show that such motifs can be utilized to address important folding issues such as detecting important folding events, and structurally characterizing a folding pathway.